Masked arrays are NumPy arrays that may have missing or invalid entries. The `numpy.ma` module provides a nearly work-alike replacement for NumPy that supports data arrays with masks.
Questions tagged [masked-array]
151 questions
0
votes
1 answer
Why does a dot product of two masked vectors in numpy return an oddly shaped array?
I have the following code:
result = np.ma.dot( array1, masked_array2 )
Which gives something like this:
masked_array(data = 24.681441709536468,
mask = False,
fill_value = 1e+20)
result.data.shape gives:
()
I can access the value…
Anton Fedoruk
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votes
0 answers
Memory issues when finding masked median of masked ndarray
I am trying to align 60 images by creating a cube (with larger dimensions than the images; 60x3000x4000) that stores information about each image and how much it is shifted by. I then combine that by finding the masking the cube for any 0 values and…
S95
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votes
1 answer
Why are the return types of the numpy sum and mean function behaving differently when fed with a masked array?
Debugging a python package I've come across the following issue:
In the pathological case that I feed the numpy mean function with a masked array, the return type is a masked array:
>>> import numpy as np
>>> import numpy.ma as ma
>>>…
momme
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- 9
0
votes
1 answer
python - modify part of a masked array inside a function
I need to modify part of a masked array inside a function eg:
import numpy.ma as ma
arr_2d = ma.masked_all((5,5))
arr_3d = ma.masked_all((5,5,5))
arr_3d[0,1] = 5
def func1(arr, val):
arr[:] = val
looks simple enough but then...
>>>…
fred
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0 answers
Unmasking list with .filled()
I have a masked list such as:
[masked_array(data = [ 0.12963803],
mask = False,
fill_value = 1e+20),
masked_array(data = 0.22379663389345425,
mask = False,
fill_value = 1e+20),
masked_array(data = [ 0.13113253],
…
Py-ser
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3 answers
python fancy indexing with a boolean masked array
I have a numpy masked array of data:
data = masked_array(data = [7 -- 7 1 8 -- 1 1 -- -- 3 -- -- 3 --],
mask = [False True False False False True False False True True False True True False True])
I have a flag of a specific…
JoVe
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0
votes
1 answer
Replace values in masked numpy array not working
I have the foll. masked array in numpy called arr with shape (50, 360, 720):
masked_array(data =
[[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
...,
[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
[-- -- --…
user308827
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2 answers
When does advanced indexing on structured masked arrays *really* return a copy?
When I have a structured masked array with boolean indexing, under what conditions do I get a view and when do I get a copy? The documentation says that advanced indexing always returns a copy, but this is not true, since something like X[X>0]=42…
gerrit
- 24,025
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2 answers
np.ma.argmax on masked array of unsigned integer dtype returns wrong result in numpy 1.11.0
I stumbled over a strange fact concerning masked unsigned integer arrays and np.ma.argmax.
Consider the following array:
>>> marr = np.ma.array(np.array([[2,2,2], [3,3,3], [1,1,1]]), mask=False, dtype=np.uint16)
>>> marr
masked_array(data =
[[2 2…
MSeifert
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2 answers
Averaging numpy masked array over multiple dimensions
It is possible to compute the average of a numpy array over multiple dimensions, as in eg. my_ndarray.mean(axis=(1,2)).
However, it does not seem to work with a masked array:
>>> import numpy as np
>>> a = np.random.randint(0, 10, (2, 2, 2))
>>>…
Arcturus B
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0
votes
1 answer
How to apply a mask to a DataFrame in Python?
My dataset named ds_f is a 840x57 matrix which contains NaN values. I want to forecast a variable with a linear regression model but when I try to fit the model, I get this message "SVD did not converge":
X = ds_f[ds_f.columns[:-1]]
y =…
florian
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0 answers
Is there a "maskna" and "skipna" in numpy python
I have been searching the web for NaN in Python Numpy arrays and found some things I cannot reproduce. I am using the Anaconda distribution with numpy.version.version == 1.10.4
from numpy import NA as NA
only gets me a "cannot import NA". This NA…
cowiie
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- 1
-1
votes
1 answer
What is the best way to initialise a NumPy masked array with an existing mask?
I was expecting to just say something like
ma.zeros(my_shape, mask=my_mask, hard_mask=True)
(where the mask is the correct shape) but ma.zeros (or ma.ones or ma.empty) rather surprisingly doesn't recognise the mask argument. The simplest I've come…
Matthew Collett
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-2
votes
1 answer
Why some data is missing on a figure when I define the axes? My dataset is a DataArray and some values are masked
I would like to be able to define my axis and not lose information. Currently, I am missing the last data point in both dimensions I defined (see figure).
DATA = xr.DataArray(np.random.rand(74,13),dims=('section','lag'))
DATA =…
Anne Sophie
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votes
1 answer
Equivalent of np.array split for masked array
numpy.ma.split_array does not exist.
Consequently, does the following code works as intended if arr is a masked array?
np.array_split(arr, multiprocessing.cpu_count())
If not, how should I define a function split_masked_array to achieve similar…
WaterFox
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